Increasing hydrocarbon reserves by finding new resources in frontier areas and improving recovery in the mature fields, to meet the high energy demands, is very challenging for the oil industry. Reservoir characterization and heterogeneity studies play an important role in better understanding reservoir performance to meet this industry goal. This study was conducted on the Boonsville Bend Conglomerate reservoir system located in the Fort Worth Basin in central-north Texas. The primary reservoir is characterized as highly heterogeneous conglomeratic sandstone. To find more potential and optimize the field exploitation, it’s critical to better understand the reservoir connectivity and heterogeneity. The goal of this multidisciplinary study was to quantify the permeability heterogeneity of the target reservoir by integrating core, well log and 3D seismic data.
A set of permeability coefficients, variation coefficient, dart coefficient, and contrast coefficient, was defined in this study to quantitatively identify the reservoir heterogeneity levels, which can be used to characterize the intra-bed and inter-bed heterogeneity. Post-stack seismic inversion was conducted to produce the key attribute, acoustic impedance, for the calibration of log properties with seismic. The inverted acoustic impedance was then used to derive the porosity volume in Emerge (the module from Hampson Russell) by means of single and multiple attributes transforms and neural network. Establishment of the correlation between permeability and porosity is critical for the permeability conversion, which was achieved by using the porosity and permeability pairs measured from four cores. Permeability volume was then converted by applying this correlation. Finally, the three heterogeneity coefficients were applied to the permeability volume to quantitatively identify the target reservoir heterogeneity. It proves that the target interval is highly heterogeneous both vertically and laterally. The heterogeneity distribution was obtained, which can help optimize the field exploitation or infill drilling designs.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/149473 |
| Date | 03 October 2013 |
| Creators | Song, Qian |
| Contributors | Sun, Yuefeng, Pope, Michael, Ayers, Walter |
| Source Sets | Texas A and M University |
| Language | English |
| Detected Language | English |
| Type | Thesis, text |
| Format | application/pdf |
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